Literature DB >> 21517211

Neural encoding of relative position.

Kenneth J Hayworth1, Mark D Lescroart, Irving Biederman.   

Abstract

Late ventral visual areas generally consist of cells having a significant degree of translation invariance. Such a "bag of features" representation is useful for the recognition of individual objects; however, it seems unable to explain our ability to parse a scene into multiple objects and to understand their spatial relationships. We review several schemes (e.g., global features and serial attention) for how to reconcile bag-of-features representation with our ability to understand relationships; we review structural description theories that, in contrast, suggest that a neural binding mechanism assigns the features of each object in a scene to a separate "slot" to which relational information for that object is explicitly bound. Four functional magnetic resonance imaging-adaptation experiments assessed how ventral stream regions respond to rearrangements of two objects in a minimal scene that depict scene translations and relational changes. Changes of relative position (e.g., elephant above bus changing to bus above elephant) produced larger releases of adaptation in the anterior lateral occipital complex (LOC) than physically equivalent translations, providing evidence that spatial relations are explicitly encoded in the anterior LOC in agreement with structural description theories.

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Year:  2011        PMID: 21517211     DOI: 10.1037/a0022338

Source DB:  PubMed          Journal:  J Exp Psychol Hum Percept Perform        ISSN: 0096-1523            Impact factor:   3.332


  14 in total

1.  Higher level visual cortex represents retinotopic, not spatiotopic, object location.

Authors:  Julie D Golomb; Nancy Kanwisher
Journal:  Cereb Cortex       Date:  2011-12-20       Impact factor: 5.357

2.  Multisensory Part-based Representations of Objects in Human Lateral Occipital Cortex.

Authors:  Goker Erdogan; Quanjing Chen; Frank E Garcea; Bradford Z Mahon; Robert A Jacobs
Journal:  J Cogn Neurosci       Date:  2016-02-26       Impact factor: 3.225

3.  What can we learn about visual attention to multiple words from the word-word interference task?

Authors:  Claudio Mulatti; Lisa Ceccherini; Max Coltheart
Journal:  Mem Cognit       Date:  2015-01

4.  Toward an Integration of Deep Learning and Neuroscience.

Authors:  Adam H Marblestone; Greg Wayne; Konrad P Kording
Journal:  Front Comput Neurosci       Date:  2016-09-14       Impact factor: 2.380

5.  Task- and domain-specific modulation of functional connectivity in the ventral and dorsal object-processing pathways.

Authors:  Frank E Garcea; Quanjing Chen; Roger Vargas; Darren A Narayan; Bradford Z Mahon
Journal:  Brain Struct Funct       Date:  2018-03-13       Impact factor: 3.270

6.  Spatial encoding and underlying circuitry in scene-selective cortex.

Authors:  Shahin Nasr; Kathryn J Devaney; Roger B H Tootell
Journal:  Neuroimage       Date:  2013-07-17       Impact factor: 6.556

Review 7.  Beyond the feedforward sweep: feedback computations in the visual cortex.

Authors:  Gabriel Kreiman; Thomas Serre
Journal:  Ann N Y Acad Sci       Date:  2020-02-28       Impact factor: 5.691

8.  Renewing the respect for similarity.

Authors:  Shimon Edelman; Reza Shahbazi
Journal:  Front Comput Neurosci       Date:  2012-07-13       Impact factor: 2.380

9.  Distinguishing Target From Distractor in Stroop, Picture-Word, and Word-Word Interference Tasks.

Authors:  Xenia Schmalz; Barbara Treccani; Claudio Mulatti
Journal:  Front Psychol       Date:  2015-12-15

10.  Dynamically partitionable autoassociative networks as a solution to the neural binding problem.

Authors:  Kenneth J Hayworth
Journal:  Front Comput Neurosci       Date:  2012-09-28       Impact factor: 2.380

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